Molecular classification of colon cancer:new insights

Rodrigo DienstmannJul 2019

Disclosures

Advisory role: RocheBoehringer-IngelheimNovartis

Speaker’s fee: RocheServierSymphogenMSDIPSENSanofiAmgen

Research support: MERCK

BRAF V600EBRAF non-V600

MSITMB high

POLE mutHER2 ampl

MET ampl

Gene fusion

RAS mut +/-PIK3CA/PTEN mut

PIK3CA/PTEN mut

Wild-type

anti-EGFR therapies

BRAF inh + anti-EGFR +/- MEK inh

anti-PD1/L1

double anti-HER2

Kinase inh

45% 8%

26%

8%3%3%

1%

<1%

2%

1%

2%MET inh?

MEK inh + anti-EGFR?

To be defined

To be defined

Genomic markers

Transcriptomic classification

CMS1

CMS2

CMS3

CMS4Mixed

13%

40%

25%

15%

7%

BULK-TUMOR subtypes (primary CRC)

Consensus Molecular Subtype (CMS) groups

15%

¾ MSI

BRAF mut

BRAF mut-like

Immune infiltration

Immune-activated

Right-sided

40%

CIN

Epithelial

WNT/MYC

EGFR/ligands high

Immune-desert

Left-sided

13%

¾ CIN

Epithelial

RAS mut

BRAF mut-like

Metabolic

Immune-mixed

Right-sided

25%

CIN

Mesechymal

TGFß, angiogenesis

Stromal infiltration

Immunosuppression

Both sides

Guinney et al, Nat Med 2015

Molecular Enrichments

Right vs. left

Loree, Clin Cancer Res 2018

Context matters

Fontana et al, Annals Oncol 2018Chang et al, Annals Oncol 2018

RF

12.7%

23.8%

7.4%

18.3%

4.4%10.2%

1.3%

21.9%

<<<<<<c

<

CMS attribution is uncertain* for most samples (63%)

…and most samples (57%) show intra-tumor heterogeneity*

* i.e. RF classifier probability < 70%

Internal circle : CMS RF classificationExternal circle : Dark : CMS RF probability > 70%; Bright : CMS RF probability < 70%

* i.e. more than 1 CMS with a (WISP-derived) weight above 20%

Internal circle : WISP subtype with heighest weightExternal circle : WISP subtype with second heighest weight (if above 20%)

<<<<<<c

Intra-tumor heterogeneity in early-stage CRC

Marisa et al, ESMO 2018

Adjusted multivariablee analysis:CMS1 / CMS4 HR: 2.17 [1.36-3.5] CMS4 / CMS1 HR: 1.79 [1.14-2.8]

Intra-tumor heterogeneity in early-stage CRC

Marisa et al, ESMO 2018

Dunne et al, Nature Commun 2017

Intra-tumor heterogeneity

Spatial stability

Tumor center Invasive front

Piskol et al, Clin Cancer Res 2019

Primary-metastasis

Stage II and III

Becht et al, Clin Cancer Res 2016

CMS1 CMS2 CMS3

CMS4

CMS1 CMS2 CMS3 CMS4

T cell chemokine

T cell inhibition

Myeloid cell

Angiogenesis

Immunosuppression

Complement

Microenvironment of CRC

CMS4

Karpinski et al, Oncotarget 2017

Microenvironment of CRC

Take-home messages

• CMS groups = not driven by content (clustering of other classifiers)

highly reproducible in cohorts of primary CRC

has biology enrichments (not unique features from

pathway and tumor microenvironment perspectives)

• CMS classifiers = technical and heterogeneity issues

CRC Consensus Molecular Subtypes: prognostic value considerations

Prognosis of CMS groups in early-stage CRC

Guinney et al, Nat Med 2015 Song et al, JAMA Oncol 2016

RFS in 1,785 stage II/III CRC RFS in 1,151 stage III CRC(NSABP C-07 trial)

Prognostic value of CMS groups in metastatic CRC

Guinney et al, Nat Med 2015 Lenz et al, J Clin Oncol 2019

Survival after relapse (n=405) Overall survival metastatic CRC (n=581)

Prognostic value of CMS groups in multivariable models

Dienstmann et al, under review

Disease free survival Cox models (all patients) (n=2,636, 769 events)

Univariate analysis Multivariable analysis

HR 95% CI P value HR 95% CI P value

Age 1.01 1 – 1.02 <0.001 1.01 1 – 1.02 <0.001

pT2/pT1 versus pT3 1.07 0.65 – 1.75 0.8 0.86 0.52 – 1.43 0.56

pT4 versus pT3 1.37 1.11 – 1.69 0.003 1.46 1.18 – 1.81 <0.001

pN1 versus pN0 1.99 1.61 – 2.46 <0.001 2.05 1.65 – 2.55 <0.001

pN2 versus pN0 3.08 2.41 – 3.93 <0.001 3.15 2.45 – 4.05 <0.001

Rectum versus left 1.03 0.76 – 1.40 0.83 0.94 0.69 – 1.29 0.72

Right versus left 0.84 0.72 – 0.97 0.02 0.86 0.73 – 1.00 0.06

MSI versus MSS 0.76 0.61 –0.93 0.008 0.88 0.7 – 1.11 0.29

KRAS mut versus wild-type 1.04 0.9 – 1.21 0.55 - - -

BRAF mut versus wild-type 0.9 0.72 - 1.13 0.35 - - -

CMS4 score 1.37 1.07 – 1.76 0.01 0.93 0.64 – 1.32 0.67

CAF infiltration score 1.6 0.93 – 2.74 0.09 2.54 1.08 – 6.02 0.03

CytoLym infiltration score 0.45 0.25 – 0.78 0.005 0.26 0.12 – 0.55 <0.001

Prognostic value of CMS groups in multivariable models

Dienstmann et al, under review

Prognostic value of CMS groups in multivariable models

Overall population (N=2,636)

Dienstmann et al, under review

Prognostic value of CMS groups in multivariable models

Dienstmann et al, under review

Prognostic value of Immunoscore in multivariable models

Pages et al, Lancet 2018

CRC Consensus Molecular Subtypes: predictive value considerations

Predictive value of CMS groups in early-stage disease

Pogue-Geile et al, ASCO 2019

Predictive value of CMS groups in early-stage disease

Pogue-Geile et al, ASCO 2019

in MOSAIC

CALGB80405 1st line KRAS wild-type RCT (n=581)

FOLFOX-cetuximab vs.

FOLFOX bevacizumab

(75%)

CMS1 > OS with

FOLFOX-bevacizumab,

CMS2 > OS with

FOLFOX-cetuximab

Custom

Nanostring

FFPE

FIRE-3 1st line RAS wild-type RCT (n=438)FOLFIRI-cetuximab vs.

FOLFIRI bevacizumab

CMS4 > OS with

FOLFIRI-cetuximab

Almac Xcell

FFPE

CAIRO2 1st line all-comers RCT (n=311)

CAPOX-bevacizumab vs.

CAPOX-bevacizumab-

cetuximab

CMS2/CMS3 > OS with

cetuximab

(RAS /BRAF wt)

IHC FFPE

MAX 1st line all-comers RCT (n=237)

Capecitabine +/-

mitomycin +/-

bevacizumab

CMS2/CMS3 > PFS with

bevacizumab

Almac Xcell

FFPE

Japan 1st line all-comers Retrospective (n=193)Oxaliplatin vs.

Irinotecan

CMS4 > PFS and OS

with IrinotecanAgilent FF

Predictive value of CMS groups in metastatic disease

Lenz et al, J Clin Oncol 2019; Stintzing et al, ASCO 2017; Trinh et al, Clinical Cancer Res 2017; Mooi et al, Annals Oncol 2018; Okita et al, Oncotarget 2018

100%

87%

CALGB 80405

Lenz et al, ASCO 2017

PFS OS

CMS1

CMS2

CMS3

CMS4

All (CMS Population)

Favors Bevacizumab Favors Bevacizumab

0.1 1 10 0.1 1 10

Favors Cetuximab

Predictive value of CMS groups in metastatic disease

CALGB 80405

Lenz et al, J Clin Oncol 2019

Predictive value of CMS groups in metastatic disease

Bevacizumab- treated Cetuximab-treated

CMS1 interaction P value < 0.001

Becht et al, Advances Immunol 2016

Microenviroment targeting in metastatic CRC

Karpinski et al, Oncotarget 2017

Microenvironment of CRC

Primary-metastasis heterogeneity?

Take-home messages

• CMS prognostic value = largely explained by tumor microenvironment

• CMS predictive value = has driver pathway enrichments (maybe not

the one that matters to a targeted/immunotherapy matched drug)

Future: combine CMS with pathway signatures

Pogue-Geile et al, ASCO 2019

RPS: recombinant proficiency score – DNA damage repair

CIN

MSI

KRA

S/N

RA

Sm

uta

tio

ns

Left

(T

um

or

Loca

tio

n)

Rig

ht

BR

AF

mu

tati

on

s

Dienstmann et al, Nat Rev Cancer 2017

Mu

tati

on

co

unt

Co

py

nu

mb

er

CMS2

Immune activationJAK-STAT activationCaspasesDNA damage repairGlutaminolysisLipodogenesisCell cycleWNT/MYC targets HER (ligands) expressionVEGF/VEGFR activationIntegrins activationTGFβ activationMesenchymal transitionComplement activationImmunosuppression

CMS3

CMS4

CMS1

Met

hyla

tio

n

Poorly immuno-

genic

Can

cer-

asso

ciat

ed fi

bro

bla

sts Highly

immuno-genic

Inflamed immuno-

suppressive

Future: Integrative CRC classification

RAS targeting in CRC

COLOSSUS project – functional subtypes of MSS RAS mutant CRC for Precision OncologyFunding: H2020 grantProject Coordinator: Annette Byrne

Scientific Leader: Rodrigo Dienstmann

CMS classifiers in the clinics

IHC FFPE

NanoString FFPE

Thanks to

Gastrointestinal Tumors GroupMolecular Prescreening Program

ODysSey Group

Ragnhild LotheJustin GuinneyJosep Tabernero